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---
base_model: airesearch/wangchanberta-base-att-spm-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: wcBERTaAttSpmm-ggTranslate-senticPolarEmotion-bully-f1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/herobye13579/huggingface/runs/1g8tmg7k)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/herobye13579/huggingface/runs/1g8tmg7k)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/herobye13579/huggingface/runs/1g8tmg7k)
# wcBERTaAttSpmm-ggTranslate-senticPolarEmotion-bully-f1
This model is a fine-tuned version of [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co./airesearch/wangchanberta-base-att-spm-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5229
- Accuracy: 0.7448
- Precision: 0.7291
- Recall: 0.7448
- F1 Score: 0.7303
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 0.551 | 1.0 | 120 | 0.5535 | 0.7427 | 0.7285 | 0.7427 | 0.7311 |
| 0.5476 | 2.0 | 240 | 0.5530 | 0.7406 | 0.7259 | 0.7406 | 0.7285 |
| 0.5352 | 3.0 | 360 | 0.5528 | 0.7354 | 0.7261 | 0.7354 | 0.7294 |
| 0.5482 | 4.0 | 480 | 0.5531 | 0.7312 | 0.7278 | 0.7312 | 0.7293 |
| 0.5386 | 5.0 | 600 | 0.5547 | 0.7228 | 0.7236 | 0.7228 | 0.7232 |
| 0.5391 | 6.0 | 720 | 0.5467 | 0.7427 | 0.7303 | 0.7427 | 0.7335 |
| 0.5495 | 7.0 | 840 | 0.5506 | 0.7395 | 0.7305 | 0.7395 | 0.7337 |
| 0.5305 | 8.0 | 960 | 0.5444 | 0.7427 | 0.7321 | 0.7427 | 0.7353 |
| 0.5183 | 9.0 | 1080 | 0.5326 | 0.7448 | 0.7320 | 0.7448 | 0.7349 |
| 0.5065 | 10.0 | 1200 | 0.5218 | 0.7479 | 0.7314 | 0.7479 | 0.7297 |
| 0.4753 | 11.0 | 1320 | 0.5207 | 0.7469 | 0.7317 | 0.7469 | 0.7330 |
| 0.4731 | 12.0 | 1440 | 0.5233 | 0.7458 | 0.7302 | 0.7458 | 0.7312 |
| 0.4828 | 13.0 | 1560 | 0.5243 | 0.7458 | 0.7302 | 0.7458 | 0.7312 |
| 0.4662 | 14.0 | 1680 | 0.5229 | 0.7458 | 0.7306 | 0.7458 | 0.7321 |
| 0.472 | 15.0 | 1800 | 0.5229 | 0.7448 | 0.7291 | 0.7448 | 0.7303 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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